An approach based on interval belief degrees and fuzzy evidential reasoning analytical algorithm is developed for multi-criteria decision problems with uncertainties. The criteria weights are represented by interval numbers and criteria values by triangular intuitionistic fuzzy numbers. The proposed approach does not need to utilize the theories such as arithmetic operations for Triangular intu...

process capability indices (pcis) can be used as an effective tool for measuring product quality and process performance. in classic quality control there are some limitations which prevent a deep and flexible analysis because of the crisp definition of pca‟s parameters. fuzzy set theory can be used to add more flexibility to process capability analyses. in this study, the fuzzy x ba and mrx ba...

Fuzzylogic,duetoitsnatureofcharacterizingtheambiguouscaseswithmultiplevalues,offersrich resourcesfordealingwithassessmentsituations,afactthatgaveusseveraltimesinpasttheimpulse toapplyitsprinciplesforsuchkindofsituations.FuzzyNumbers(FNs)playafundamentalrolein fuzzymathematics,analogoustotheroleplayedbytheordinarynumbersinclassicalma...

Recently, fuzzy linear programming problems have been considered by many. In the literature of fuzzy linear programming several models are offered and therefore some various methods have been suggested to solve these problems. One of the most important of these problems that recently has been considered; are Fully Fuzzy Linear Programming (FFLP), which all coefficients and variables of the prob...

The critical path problem is a classical and important network optimization problem appearing in many applications, especially in planning and controlling the complex projects. However the result of classical critical path method computation cannot properly match the real-world problem. This gives rise to fuzzy environment and hence we have fuzzy critical path method. In this paper, two differe...

Abstract In this paper we have investigated a fuzzy linear programming problem with fuzzy quantities which are LR triangular fuzzy numbers. The given linear programming problem is rearranged according to the satisfactory level of constraints using breaking point method. By considering the constraints, the arranged problem has been investigated for all optimal solutions connected with satisf...

Risk assessment is a popular and important tool in decision making process. Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty. Here, we consider that model parameters are affected by epistemic uncertainty. To represent epistemic uncertainty in general triangular fuzzy number or trapezoidal fuzzy numbers are u...

In this paper, we consider fuzzy inventory with backorder. First, we fuzzify the storing cost a, backorder cost b, cost of placing an order c, total demand r, order quantity q, and shortage quantity s as the triangular fuzzy numbers in the total cost. From these, we can obtain the fuzzy total cost. Using the signed distance method to defuzzify, we get the estimate of the total cost in the fuzzy...

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

In this paper a new aggregation operator for a class of LR Fuzzy Numbers i.e., Triangular Fuzzy Numbers (TFNs) in which the Land Rapex angles of the piecewise continuous linear membership function of the composite or resultant or aggregate TFN are the arithmetic means of the corresponding Land Rapex angles of the individual TFNs is proposed. The Land Rapex angles have been treated independently...